Dataiku DSSΒΆ
Welcome to the reference documentation for Dataiku Data Science Studio (DSS).
More learning resources are available at Dataiku Learn.
- Installing DSS
- Requirements
- Installing a new DSS instance
- Upgrading a DSS instance
- Other installation options
- Setting up Hadoop and Spark integration
- Setting up R integration
- Customizing DSS installation
- Installing database drivers
- Java runtime environment
- The Python environment
- Installing a DSS plugin
- Configuring LDAP authentication
- Working with proxies
- Migration operations
- DSS concepts
- Connecting to data
- Exploring your data
- Schemas, storage types and meanings
- Data preparation
- Data Visualization
- Machine learning
- The Flow
- Visual recipes
- Recipes based on code
- Code notebooks
- Webapps
- Dashboards
- Working with partitions
- DSS and Hadoop
- DSS and Spark
- Collaboration
- Plugins
- Real-time predictions
- Introduction
- Concepts
- Installing the API node
- Exposing a prediction model
- Custom prediction models
- API node user API
- Using the apinode-admin tool
- API node administration API
- High availability and scalability
- Enriching queries in real-time
- Managing versions of your endpoint
- Logging and auditing
- Health monitoring
- Automation node and bundles
- Automation scenarios, metrics, and checks
- Advanced topics
- File formats
- DSS APIs
- Security
- Operating DSS
- Tips and troubleshooting
- Release notes
- Other Documentation
- Third-party acknowledgements